An Australian cross-sectional study exploring the potential role of generative AI in high school computer programming education

Background and Context: Generative artificial intelligence (AI) tools such as ChatGPT are emerging as influential resources in education, with potential to support learning in high school programming through interactive, on-demand assistance. Objective: This cross-sectional study explored relationships between high school students’ ability to complete programming activities when permitted to use generative AI, their interest and attitude towards programming, and foundational mathematical knowledge. Method: High school students undertaking a computing course at an independent boys school in Sydney, Australia were invited to complete an online survey and attend a lab-based session to complete seven programming-related tasks of varying complexity. Findings: Eighty-six students consented; analyses of programming performance were restricted to 64 (74.4%) students who attended the lab-based session, with mathematics grades available for 63 students. Among lab participants, mean assessment score was 29.86 ± 18.91 (out of 100); interest and attitude towards programming score was 56.69 ± 20.08 (out of 92); and math score was 79.95 ± 16.88 (out of 100). There were no statistically significant differences in the assessment scores across groups with high (n = 30), moderate (n = 29), and low (n = 5) interest and attitude towards programming, or across groups with math grade A (n = 23), B (n = 27), and C or below (n = 13). Implications: Generative AI can help high school students complete programming activities, even among those without high interest and attitude towards programming or strong mathematical skills. These findings suggest that, when carefully integrated into teaching, generative AI tools can broaden student engagement in programming, while cautioning against overreliance on AI-generated solutions.